Overview

Dataset statistics

Number of variables32
Number of observations46764
Missing cells0
Missing cells (%)0.0%
Duplicate rows64
Duplicate rows (%)0.1%
Total size in memory7.3 MiB
Average record size in memory164.0 B

Variable types

Categorical24
Numeric8

Alerts

Dataset has 64 (0.1%) duplicate rowsDuplicates
consumer_complaint_narrative has a high cardinality: 46094 distinct valuesHigh cardinality
sub_product_freq is highly overall correlated with sub_product_null_flagHigh correlation
issue_freq is highly overall correlated with sub_issue_freq and 3 other fieldsHigh correlation
sub_issue_freq is highly overall correlated with issue_freq and 1 other fieldsHigh correlation
company_public_response_freq is highly overall correlated with company_public_response_null_flag and 1 other fieldsHigh correlation
company_freq is highly overall correlated with sub_product_null_flag and 2 other fieldsHigh correlation
state_freq is highly overall correlated with state_null_flag and 1 other fieldsHigh correlation
zipcode_freq is highly overall correlated with state_null_flag and 1 other fieldsHigh correlation
sub_product_null_flag is highly overall correlated with sub_product_freq and 2 other fieldsHigh correlation
issue_low_flag is highly overall correlated with issue_freqHigh correlation
sub_issue_null_flag is highly overall correlated with issue_freq and 2 other fieldsHigh correlation
company_public_response_null_flag is highly overall correlated with company_public_response_freqHigh correlation
company_public_response_low_flag is highly overall correlated with company_public_response_freqHigh correlation
company_low_flag is highly overall correlated with company_freqHigh correlation
state_null_flag is highly overall correlated with state_freq and 2 other fieldsHigh correlation
zipcode_null_flag is highly overall correlated with state_freq and 2 other fieldsHigh correlation
Not Older American, Not Servicemember is highly overall correlated with Older American and 1 other fieldsHigh correlation
Older American is highly overall correlated with Not Older American, Not ServicememberHigh correlation
Servicemember is highly overall correlated with Not Older American, Not ServicememberHigh correlation
Closed with explanation is highly overall correlated with Closed with monetary relief and 1 other fieldsHigh correlation
Closed with monetary relief is highly overall correlated with Closed with explanationHigh correlation
Closed with non-monetary relief is highly overall correlated with Closed with explanationHigh correlation
timely_response is highly imbalanced (79.2%)Imbalance
sub_product_low_flag is highly imbalanced (64.9%)Imbalance
company_public_response_low_flag is highly imbalanced (76.7%)Imbalance
state_null_flag is highly imbalanced (97.1%)Imbalance
state_low_flag is highly imbalanced (52.8%)Imbalance
zipcode_null_flag is highly imbalanced (97.1%)Imbalance
Older American is highly imbalanced (56.0%)Imbalance
Older American, Servicemember is highly imbalanced (90.5%)Imbalance
Servicemember is highly imbalanced (64.6%)Imbalance
Closed is highly imbalanced (82.0%)Imbalance
Closed with monetary relief is highly imbalanced (61.9%)Imbalance
Untimely response is highly imbalanced (93.4%)Imbalance
consumer_complaint_narrative is uniformly distributedUniform
days_between_receipt_and_sent has 34255 (73.3%) zerosZeros

Reproduction

Analysis started2023-01-06 21:37:08.536326
Analysis finished2023-01-06 21:38:41.700892
Duration1 minute and 33.16 seconds
Software versionpandas-profiling vv3.6.1
Download configurationconfig.json

Variables

consumer_complaint_narrative
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct46094
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company! THIS IS NOT MY DEBT! I WANT THIS ACCOUNT REMOVED FROM MY CREDIT REPORT AND THIS COMPANY TO STOP CONTACTING ME IMMEDIATELY!
 
25
I have sent several requests to Experian requesting an investigation of my accounts. It has been months and I still have not received a response to my concerns. The only thing I have received is some automated rejection letter stating that they wo n't do anything to help me ( please see attached ). This has to be a violation of my rights. I feel like I 've already wasted so much time just trying to get Experian to look at the errors on my credit report and I 'm so frustrated that Experian is intentionally not responding to my inquiries. I need to have this issue resolved immediately. There are many things I need to do with my life and they all involve my credit. But I am not able to move forward all because of this credit bureau!
 
20
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company! THIS IS NOT MY DEBT!
 
19
I have been a victim of Identity Theft. I have been trying to work with the Credit Reporting Agency but they are refusing to honor my valid identity theft case thus these incorrect/fraudulent items are still on my credit report and they must be removed immediately but they are do not belong to me. I have provided all of the proof to show that I was a victim of Identity Theft and that to the best of my knowledge these fraudulent accounts do not belong to me. Please take immediate action on my behalf so I can have these items removed, deleted and permanently blocked from my credit report, so that I can get back on track to a normal life. Regards
 
16
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company!
 
11
Other values (46089)
46673 

Length

Max length5153
Median length3260
Mean length1037.4295
Min length10

Characters and Unicode

Total characters48514354
Distinct characters99
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45690 ?
Unique (%)97.7%

Sample

1st rowDear Sir or Madam, Ever since XXXX XXXX XXXX sold our Mortgage Loan to XXXX, we have had nothing but problems. My husband and I back in 2009, tried to modify the loan. This was an absolute nightmare. After submitting information several times and going through numerous " scheduling '' of calls with Loan counselors, who when I finally got to talk to them, had nothing of substance to discuss or help me with and offered no guidance or help. They would tell me that I needed to get certain pieces of info. and schedule yet another call ( which were always 2 weeks later ) and take it from there, then it was like XXXX XXXX XXXX ... .. I would schedule call after call just to discuss separate pieces of my Loan Mod. Application. It made NO SENSE! I got nowhere and gave up. I have a file 3 inches thick with my application, with forms and notes and all the back up info that I scanned to them, which they claimed to never have received ... .. I finally gave up. With my husband laid off due the construction industry being very slow at the time, I decided to file bankruptcy. I believe that had I was given the chance to modify, I could have avoided filing for Chapter XXXX. About 4 years later or so, here I am now, and the loan was sold to Nationstar. Again, I am having issues which again stem from XXXX. I have had to have my bankruptcy attorney help me to get a simple answer about why my escrows all of the sudden went up {$300.00} per month! My taxes did not go up. The only thing that I did do was switch my Homeowners Insurer and my payment should have only gone up around {$30.00} a month, or less!! XXXX sent me XXXX copies of an Escrow Analysis which was XXXX or so pages, which raised my payment upwards of {$300.00} per month, and did not offer a clear reason why. I called and was given no explanation by XXXX. As a matter of fact, I was told " you were not supposed to see that ''. I did not know what that meant. I received a letter from XXXX after this saying my loan was transferred to NationStar. I called them for explanation and guidance, and got fuzzy answers from them. Nobody could explain the payment increase. They even told my attorney that they did not know what happened. I kind of let it go for a while, and then when I called in my payment for that month they would not take my normal payment. They would only take the payment with the increase of {$300.00}. I did not want to pay that because I did not agree with it and it is not in my budget being in Chapter XXXX, plus I was offered no reason why the payment increased! So, for the next several months I had to mail in my payments ( my normal payment NOT the payment with their increase calculations ), and my payments were late. In the meantime, I am having an attorney help me. After approximately 7 months, my attorney FINALLY got an answer ... .. my payment did increase but buy {$90.00}, not {$300.00} - however, I still do not why! I have the form and my loan number is crossed out, so I do n't even know if it is mine .... Right now, I am so confused. I have now incurred attorneys fees and late fees due to this error. I do not think I should be obligated to pay these fees due to XXXX error and Nationstar 's ignorance in its inability to explain the increase. Is there anything you can do to help me.
2nd rowon XXXX XXXX, 2015 there was an ACH transaction withdrawal from my account without my permission for {$750.00} to a company bamed XXXX. this ACH transaction caused my business account to go into a negative balance. when I noticed the transaction on XXXX XXXX, 2015 I immediately called my bank and spoke to the claims department. I explain the situation that this was a fraudulent activity that I have no knowledge or no relations to XXXX or the bank that was involved as well named fifth third Bank in Michigan. XXXX XXXX filed the claim XXXX XXXX filed the claims for me and told me I would receive a refund in 12 hours or up to 1 to 2 business days. When I followed up on XXXX XXXX, 2015 with XXXX who holds my business account at approximately XXXX XXXX I was told that my claim was denied because I needed to make a claim within 24 hours of the transaction. before finding out that my claim was denied I have been going back-and-forth with the XXXX the claim department and the claim department from fifth third Bank. From here I was able to claim the company ID and the trace number in regards to this transaction. after finding out that my claim was denied I had spoke to my branch manager at XXXX to have a representative called the claim department in regards to the situation. I was able to retrieve my contract that I had signed with the business account. On Monday, XXXX XXXX, 2015 I have to call the XXXX claim department and they will be contacting fifth third bank with me on the line in regards to this transaction. I have filed a claim two times more after the my claim was denied.
3rd rowMy wife has not received a paper bill from Chase Card Services for an Amazon account in two years. I was informed that the account had paperless billing. The card is basically maxed out with late fees despite receiving payments and I had no idea.
4th rowthe company m & M funding has been harassing from the time i bought my first vehicle in 2011 from them the would call me when the declaration page on my insurance would expire instead of calling the insurance company they also lied to me had me pay for gap on my vehicle than when my son wrecked my vehicle they told me they were not doing gap because of the payment process of gap they call me when im at work all the time im about ready to be fired i can not answer my phone at work there former manager told me XXXX time that he did n't think i had insurance because he was having a hard time getting the declaration page from the insurance company he basically said i was lying he told me his daughter worked for the same insurance company i had and i and i lying about how long it was going to take for me to get the paperwork i talked to XXXX at the company on XXXX/XXXX/2015 at XXXX our time and than he called me again today for the same thing i already talked to him about i would like to own both of my vehicles from this company there is other things they have called continuously about but i ca n't remember than all right now. they are also very rude with there clients they are always got new employees so you never know who your talking to from XXXX month to the next so everyone at the company knows your business its not just XXXX person working on the file.
5th rowCan my reverse mortgage lender refuse to continue/renew my current property tax loan? Hi, My lender, Wells Fargo, is telling me that they can not continue/renew my current loan that they had advanced for property taxes that were due. They have informed me that, unless I repay the full balance, they will begin foreclosure proceedings on my home now. I am told that HUD XX/XX/2015 issued new rules to lenders affecting reverse mortgage loans. Specifically, in my case, I now no longer meet the " XXXX '' requirement ; I am told that I am at XXXX %. I am XXXX years old and do n't want to lose my home. My husband XXXX last year, he was XXXX and had XXXX XXXX. We have never been late on any payments to Wells Fargo, and I can comfortably meet all my expenses, including the payment that I make to Wells Fargo for back property taxes each month. This change of rules came as a total surprise. I hate to say this, but I feel that I have been misled, unwittingly perhaps. To their credit, Wells Fargo has assigned a financial counselor to my case, XXXX XXXX, which I appreciate. I am told by XXXX XXXX, this HUD rule change is not only a problem for me but also pertains to many other seniors in our country who have property tax and/or home insurance advances from their lenders. I suspect that many of these seniors are not able to speak up for themselves and will, indeed, loose their homes.

Common Values

ValueCountFrequency (%)
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company! THIS IS NOT MY DEBT! I WANT THIS ACCOUNT REMOVED FROM MY CREDIT REPORT AND THIS COMPANY TO STOP CONTACTING ME IMMEDIATELY! 25
 
0.1%
I have sent several requests to Experian requesting an investigation of my accounts. It has been months and I still have not received a response to my concerns. The only thing I have received is some automated rejection letter stating that they wo n't do anything to help me ( please see attached ). This has to be a violation of my rights. I feel like I 've already wasted so much time just trying to get Experian to look at the errors on my credit report and I 'm so frustrated that Experian is intentionally not responding to my inquiries. I need to have this issue resolved immediately. There are many things I need to do with my life and they all involve my credit. But I am not able to move forward all because of this credit bureau! 20
 
< 0.1%
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company! THIS IS NOT MY DEBT! 19
 
< 0.1%
I have been a victim of Identity Theft. I have been trying to work with the Credit Reporting Agency but they are refusing to honor my valid identity theft case thus these incorrect/fraudulent items are still on my credit report and they must be removed immediately but they are do not belong to me. I have provided all of the proof to show that I was a victim of Identity Theft and that to the best of my knowledge these fraudulent accounts do not belong to me. Please take immediate action on my behalf so I can have these items removed, deleted and permanently blocked from my credit report, so that I can get back on track to a normal life. Regards 16
 
< 0.1%
This company continues to report on my credit report after I sent them a letter telling them that this account was not mine and I have no idea what it is or who it belongs to! I asked for proof of a signed contract, I asked for a license to collect in my state, I asked for copies of all information referenced for this debt and still to date, I have not received anything but harassment from this company! 11
 
< 0.1%
While checking my personal credit report, I noticed an unauthorized and fraudulent credit inquiry made by XXXX on or about XX/XX/XXXX on Transunion. I did not authorized anyone employed by this company to make any inquiry and view my credit report. XXXX has violated the Fair Credit Reporting Act Section 1681b ( c ). They were not legally entitled to make this fraudulent inquiry. This is a serious breach of my privacy rights. I have requested that they mail me a copy of my signed authorization form that gave them the right to view my credit within five ( 5 ) business days so that I can verify its validity and advised them that if they can not provide me with proof that I authorized them to view my credit report then I am demanding that they contact the credit bureaus immediately and have them remove the unauthorized and fraudulent hard inquiry immediately. I also requested that they remove my personal information from their records. My Social Security # is XXXX and my Date of Birth is XX/XX/XXXX in case it is needed to locate the fraudulent inquiry in their system. 11
 
< 0.1%
I have been a victim of Identity Theft, and I am trying to dispute inaccurate items on my credit report. 10
 
< 0.1%
In XXXX, I requested my free annual credit report. After viewing my credit report, I noticed over XXXX credit/loan inquiries on my account that was not authorized by me. I contacted each company and was told that there was not any account open under my information. I explained that I have a hard inquiry on my credit report and need it removed as soon as possible so that I could apply for a home. I was told that the inquiries would be removed from my credit report. As of XXXX/XXXX/XXXX, none of the inquiries have been removed dating back to XXXX. I had a initial fraud alert placed on my report on XXXX XXXX, so if any credit reports are being pulled with my information, I was to be contacted by the company before any action was taken place. I just want the inquiries to be removed so that my scores and credit is not being impacted any longer. I would like to purchase a house, but until all of the inquires are removed I will not be approved with XXXX inquires on my credit report. 8
 
< 0.1%
I am filing this complaint because I think what Experian is doing to me is wrong, unethical and may be against the law. A letter was mailed to Experian on or around [ XXXX/XXXX/15 ]. I clearly stated my concerns to them regarding inaccurate, questionable or unverifiable information listed on my credit report. I also provided a clear copy of my ID, proof of my social security number and a proof of my current mailing address. On [ XXXX/XXXX/15 ] I received a notice from Experian stating the following : '' We received a suspicious request in the mail regarding your personal credit report and determined that it was not sent by you. Suspicious requests are reviewed by Experian security personnel who work regularly with law enforcement officials and regulatory agencies to identify fraudulent and deceptive correspondence purporting to originate from consumers. In an effort to safeguard your personal credit information from fraud, we will not be initiating any disputes based on the suspicious correspondence. Experian will apply this same policy to any future suspicious requests that we receive regarding your personal credit information, but we will not send additional notices to you of suspicious correspondence. If you believe that information in your personal credit report is inaccurate or incomplete, please visit our website at experian.com/validate dispute or call us at XXXX ( XXXX ) XXXX to speak directly to an Experian consumer assistance representative. " However, an Experian confirmation number was not even provided on this notice. I can not imagine what could have possibly been " suspicious '' about my correspondence to Experian. I should not have to spend endless hours on phone calling the credit bureau back and forth attempting to resolve the issues on my credit report! I am filing this complaint because Experian will not respond to any letters that I am sending in. I 'm sure this could be a violation of my rights and Experian should not be deliberately disregarding my concerns! 7
 
< 0.1%
While checking my personal credit report, I noticed an unauthorized and fraudulent credit inquiry made by XXXX on or about XX/XX/XXXX on Experian. I did not authorized anyone employed by this company to make any inquiry and view my credit report. XXXX has violated the Fair Credit Reporting Act Section 1681b ( c ). They were not legally entitled to make this fraudulent inquiry. This is a serious breach of my privacy rights. I have requested that they mail me a copy of my signed authorization form that gave them the right to view my credit within five ( 5 ) business days so that I can verify its validity and advised them that if they can not provide me with proof that I authorized them to view my credit report then I am demanding that they contact the credit bureaus immediately and have them remove the unauthorized and fraudulent hard inquiry immediately. I also requested that they remove my personal information from their records. My Social Security # is XXXX and my Date of Birth is XX/XX/XXXX in case it is needed to locate the fraudulent inquiry in their system. 7
 
< 0.1%
Other values (46084) 46630
99.7%

Length

2023-01-06T15:38:42.215990image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
xxxx 379167
 
4.3%
the 366129
 
4.1%
i 333704
 
3.8%
to 305368
 
3.4%
and 241698
 
2.7%
a 182400
 
2.1%
my 178986
 
2.0%
167695
 
1.9%
of 140308
 
1.6%
that 138307
 
1.6%
Other values (58353) 6462201
72.6%

Most occurring characters

ValueCountFrequency (%)
8897109
18.3%
e 4388215
 
9.0%
t 3440429
 
7.1%
a 2995549
 
6.2%
o 2617275
 
5.4%
n 2547703
 
5.3%
i 2203753
 
4.5%
r 1969851
 
4.1%
X 1881746
 
3.9%
s 1861995
 
3.8%
Other values (89) 15710729
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34387563
70.9%
Space Separator 8897109
 
18.3%
Uppercase Letter 3518999
 
7.3%
Other Punctuation 990601
 
2.0%
Decimal Number 381875
 
0.8%
Control 111965
 
0.2%
Close Punctuation 75340
 
0.2%
Open Punctuation 73172
 
0.2%
Currency Symbol 44701
 
0.1%
Dash Punctuation 30916
 
0.1%
Other values (3) 2113
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4388215
12.8%
t 3440429
 
10.0%
a 2995549
 
8.7%
o 2617275
 
7.6%
n 2547703
 
7.4%
i 2203753
 
6.4%
r 1969851
 
5.7%
s 1861995
 
5.4%
h 1633951
 
4.8%
d 1572471
 
4.6%
Other values (17) 9156371
26.6%
Uppercase Letter
ValueCountFrequency (%)
X 1881746
53.5%
I 398871
 
11.3%
T 160208
 
4.6%
A 123484
 
3.5%
E 96415
 
2.7%
C 91651
 
2.6%
S 91236
 
2.6%
O 76109
 
2.2%
N 70704
 
2.0%
R 57307
 
1.6%
Other values (16) 471268
 
13.4%
Other Punctuation
ValueCountFrequency (%)
. 486251
49.1%
, 238481
24.1%
' 95317
 
9.6%
/ 86498
 
8.7%
" 20634
 
2.1%
! 14455
 
1.5%
: 11902
 
1.2%
? 10256
 
1.0%
; 7060
 
0.7%
# 5763
 
0.6%
Other values (5) 13984
 
1.4%
Decimal Number
ValueCountFrequency (%)
0 185822
48.7%
1 51541
 
13.5%
2 42123
 
11.0%
5 34025
 
8.9%
3 18655
 
4.9%
4 13326
 
3.5%
6 12161
 
3.2%
9 8189
 
2.1%
7 8091
 
2.1%
8 7942
 
2.1%
Math Symbol
ValueCountFrequency (%)
+ 696
47.6%
= 506
34.6%
~ 104
 
7.1%
| 102
 
7.0%
> 33
 
2.3%
< 20
 
1.4%
Control
ValueCountFrequency (%)
111945
> 99.9%
17
 
< 0.1%
€ 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
{ 41080
56.1%
( 31504
43.1%
[ 588
 
0.8%
Close Punctuation
ValueCountFrequency (%)
} 41077
54.5%
) 33674
44.7%
] 589
 
0.8%
Currency Symbol
ValueCountFrequency (%)
$ 44698
> 99.9%
¢ 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8897109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30916
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 590
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37906562
78.1%
Common 10607792
 
21.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4388215
 
11.6%
t 3440429
 
9.1%
a 2995549
 
7.9%
o 2617275
 
6.9%
n 2547703
 
6.7%
i 2203753
 
5.8%
r 1969851
 
5.2%
X 1881746
 
5.0%
s 1861995
 
4.9%
h 1633951
 
4.3%
Other values (43) 12366095
32.6%
Common
ValueCountFrequency (%)
8897109
83.9%
. 486251
 
4.6%
, 238481
 
2.2%
0 185822
 
1.8%
111945
 
1.1%
' 95317
 
0.9%
/ 86498
 
0.8%
1 51541
 
0.5%
$ 44698
 
0.4%
2 42123
 
0.4%
Other values (36) 368007
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48514345
> 99.9%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8897109
18.3%
e 4388215
 
9.0%
t 3440429
 
7.1%
a 2995549
 
6.2%
o 2617275
 
5.4%
n 2547703
 
5.3%
i 2203753
 
4.5%
r 1969851
 
4.1%
X 1881746
 
3.9%
s 1861995
 
3.8%
Other values (86) 15710720
32.4%
None
ValueCountFrequency (%)
â 3
33.3%
€ 3
33.3%
¢ 3
33.3%

timely_response
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
1
45233 
0
 
1531

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%

Length

2023-01-06T15:38:42.748046image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:43.128308image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%

Most occurring characters

ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 45233
96.7%
0 1531
 
3.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
35876 
1
10888 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%

Length

2023-01-06T15:38:43.418554image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:43.784452image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%

Most occurring characters

ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35876
76.7%
1 10888
 
23.3%
Distinct91
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9371953
Minimum0
Maximum290
Zeros34255
Zeros (%)73.3%
Negative0
Negative (%)0.0%
Memory size365.5 KiB
2023-01-06T15:38:44.214191image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile9
Maximum290
Range290
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.0858792
Coefficient of variation (CV)3.1415931
Kurtosis201.77553
Mean1.9371953
Median Absolute Deviation (MAD)0
Skewness9.1019451
Sum90591
Variance37.037926
MonotonicityNot monotonic
2023-01-06T15:38:44.793091image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34255
73.3%
2 1927
 
4.1%
1 1662
 
3.6%
3 1487
 
3.2%
5 1483
 
3.2%
4 1439
 
3.1%
6 1040
 
2.2%
7 708
 
1.5%
8 334
 
0.7%
9 213
 
0.5%
Other values (81) 2216
 
4.7%
ValueCountFrequency (%)
0 34255
73.3%
1 1662
 
3.6%
2 1927
 
4.1%
3 1487
 
3.2%
4 1439
 
3.1%
5 1483
 
3.2%
6 1040
 
2.2%
7 708
 
1.5%
8 334
 
0.7%
9 213
 
0.5%
ValueCountFrequency (%)
290 1
< 0.1%
189 1
< 0.1%
186 1
< 0.1%
163 1
< 0.1%
157 1
< 0.1%
106 1
< 0.1%
105 1
< 0.1%
102 1
< 0.1%
96 1
< 0.1%
95 1
< 0.1%

sub_product_freq
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.27170287
Minimum-1
Maximum0.098494568
Zeros0
Zeros (%)0.0%
Negative14318
Negative (%)30.6%
Memory size365.5 KiB
2023-01-06T15:38:45.306575image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median0.031028141
Q30.055983235
95-th percentile0.098494568
Maximum0.098494568
Range1.0984946
Interquartile range (IQR)1.0559832

Descriptive statistics

Standard deviation0.48438322
Coefficient of variation (CV)-1.7827682
Kurtosis-1.2943235
Mean-0.27170287
Median Absolute Deviation (MAD)0.027478402
Skewness-0.83334309
Sum-12705.913
Variance0.23462711
MonotonicityNot monotonic
2023-01-06T15:38:45.811140image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
-1 14318
30.6%
0.09849456847 4606
 
9.8%
0.07901377128 3695
 
7.9%
0.05718073732 2674
 
5.7%
0.05598323497 2618
 
5.6%
0.05281840732 2470
 
5.3%
0.04199811821 1964
 
4.2%
0.04135659909 1934
 
4.1%
0.0364810538 1706
 
3.6%
0.03511247969 1642
 
3.5%
Other values (32) 9137
19.5%
ValueCountFrequency (%)
-1 14318
30.6%
0.0001069198529 5
 
< 0.1%
0.000149687794 14
 
< 0.1%
0.0001924557352 9
 
< 0.1%
0.0002138397058 10
 
< 0.1%
0.0002352236763 11
 
< 0.1%
0.0002779916175 13
 
< 0.1%
0.0002993755881 14
 
< 0.1%
0.0003421435292 16
 
< 0.1%
0.0004704473527 44
 
0.1%
ValueCountFrequency (%)
0.09849456847 4606
9.8%
0.07901377128 3695
7.9%
0.05718073732 2674
5.7%
0.05598323497 2618
5.6%
0.05281840732 2470
5.3%
0.04199811821 1964
4.2%
0.04135659909 1934
4.1%
0.0364810538 1706
 
3.6%
0.03511247969 1642
 
3.5%
0.03102814131 1451
 
3.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
32446 
1
14318 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%

Length

2023-01-06T15:38:46.673440image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:47.035197image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%

Most occurring characters

ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32446
69.4%
1 14318
30.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
43674 
1
 
3090

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

Length

2023-01-06T15:38:47.374313image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:47.760672image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43674
93.4%
1 3090
 
6.6%

issue_freq
Real number (ℝ)

Distinct79
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05544101
Minimum2.1383971 × 10-5
Maximum0.12496792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size365.5 KiB
2023-01-06T15:38:48.140685image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum2.1383971 × 10-5
5-th percentile0.0041484903
Q10.015289539
median0.03323069
Q30.097831665
95-th percentile0.12496792
Maximum0.12496792
Range0.12494654
Interquartile range (IQR)0.082542126

Descriptive statistics

Standard deviation0.044829497
Coefficient of variation (CV)0.80859813
Kurtosis-1.5134323
Mean0.05544101
Median Absolute Deviation (MAD)0.027585322
Skewness0.38475925
Sum2592.6434
Variance0.0020096838
MonotonicityNot monotonic
2023-01-06T15:38:48.720290image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.124967924 5844
 
12.5%
0.1119878539 5237
 
11.2%
0.09783166538 4575
 
9.8%
0.07719613378 3610
 
7.7%
0.044328971 2073
 
4.4%
0.04150628689 1941
 
4.2%
0.03323069027 1554
 
3.3%
0.02953126336 1381
 
3.0%
0.02489094175 1164
 
2.5%
0.02474125396 1157
 
2.5%
Other values (69) 18228
39.0%
ValueCountFrequency (%)
2.138397058 × 10-51
 
< 0.1%
6.415191173 × 10-515
< 0.1%
0.0001069198529 5
 
< 0.1%
0.0001283038235 6
 
< 0.1%
0.000149687794 14
< 0.1%
0.0001924557352 9
 
< 0.1%
0.0002138397058 10
 
< 0.1%
0.0002352236763 22
< 0.1%
0.0002779916175 26
0.1%
0.0002993755881 14
< 0.1%
ValueCountFrequency (%)
0.124967924 5844
12.5%
0.1119878539 5237
11.2%
0.09783166538 4575
9.8%
0.07719613378 3610
7.7%
0.044328971 2073
 
4.4%
0.04150628689 1941
 
4.2%
0.03323069027 1554
 
3.3%
0.02953126336 1381
 
3.0%
0.02489094175 1164
 
2.5%
0.02474125396 1157
 
2.5%

issue_low_flag
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
39192 
1
7572 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

Length

2023-01-06T15:38:49.188354image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:49.575762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

Most occurring characters

ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39192
83.8%
1 7572
 
16.2%

sub_issue_freq
Real number (ℝ)

Distinct61
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.49527076
Minimum-1
Maximum0.067979642
Zeros0
Zeros (%)0.0%
Negative23712
Negative (%)50.7%
Memory size365.5 KiB
2023-01-06T15:38:50.007042image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q30.017727312
95-th percentile0.067979642
Maximum0.067979642
Range1.0679796
Interquartile range (IQR)1.0177273

Descriptive statistics

Standard deviation0.51211836
Coefficient of variation (CV)-1.0340169
Kurtosis-1.9957377
Mean-0.49527076
Median Absolute Deviation (MAD)0
Skewness0.030715809
Sum-23160.842
Variance0.26226521
MonotonicityNot monotonic
2023-01-06T15:38:50.547999image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 23712
50.7%
0.06797964246 3179
 
6.8%
0.03951757762 1848
 
4.0%
0.03293131469 1540
 
3.3%
0.02916773587 1364
 
2.9%
0.0253613891 1186
 
2.5%
0.02380035925 1113
 
2.4%
0.01813360705 848
 
1.8%
0.01772731161 829
 
1.8%
0.01563168249 731
 
1.6%
Other values (51) 10414
22.3%
ValueCountFrequency (%)
-1 23712
50.7%
0.0002779916175 13
 
< 0.1%
0.0003849114704 18
 
< 0.1%
0.0004276794115 20
 
< 0.1%
0.0004490633821 21
 
< 0.1%
0.0004704473527 22
 
< 0.1%
0.0004918313232 23
 
< 0.1%
0.0005987511761 28
 
0.1%
0.000705671029 33
 
0.1%
0.0007484389701 35
 
0.1%
ValueCountFrequency (%)
0.06797964246 3179
6.8%
0.03951757762 1848
4.0%
0.03293131469 1540
3.3%
0.02916773587 1364
2.9%
0.0253613891 1186
 
2.5%
0.02380035925 1113
 
2.4%
0.01813360705 848
 
1.8%
0.01772731161 829
 
1.8%
0.01563168249 731
 
1.6%
0.01524677102 713
 
1.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
1
23712 
0
23052 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%

Length

2023-01-06T15:38:51.000590image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:51.351318image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%

Most occurring characters

ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23712
50.7%
0 23052
49.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
39535 
1
7229 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%

Length

2023-01-06T15:38:51.686159image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:52.049285image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%

Most occurring characters

ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39535
84.5%
1 7229
 
15.5%
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.41362019
Minimum-1
Maximum0.28767856
Zeros0
Zeros (%)0.0%
Negative23834
Negative (%)51.0%
Memory size365.5 KiB
2023-01-06T15:38:52.338627image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q30.28767856
95-th percentile0.28767856
Maximum0.28767856
Range1.2876786
Interquartile range (IQR)1.2876786

Descriptive statistics

Standard deviation0.60294438
Coefficient of variation (CV)-1.4577248
Kurtosis-1.9339951
Mean-0.41362019
Median Absolute Deviation (MAD)0
Skewness0.08735506
Sum-19342.534
Variance0.36354193
MonotonicityNot monotonic
2023-01-06T15:38:52.749503image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
-1 23834
51.0%
0.2876785562 13453
28.8%
0.098836712 4622
 
9.9%
0.05572662732 2606
 
5.6%
0.01013600205 474
 
1.0%
0.009858010435 461
 
1.0%
0.009729706612 455
 
1.0%
0.007356085878 344
 
0.7%
0.007013942349 328
 
0.7%
0.003784962792 177
 
0.4%
ValueCountFrequency (%)
-1 23834
51.0%
0.0002138397058 10
 
< 0.1%
0.003784962792 177
 
0.4%
0.007013942349 328
 
0.7%
0.007356085878 344
 
0.7%
0.009729706612 455
 
1.0%
0.009858010435 461
 
1.0%
0.01013600205 474
 
1.0%
0.05572662732 2606
 
5.6%
0.098836712 4622
 
9.9%
ValueCountFrequency (%)
0.2876785562 13453
28.8%
0.098836712 4622
 
9.9%
0.05572662732 2606
 
5.6%
0.01013600205 474
 
1.0%
0.009858010435 461
 
1.0%
0.009729706612 455
 
1.0%
0.007356085878 344
 
0.7%
0.007013942349 328
 
0.7%
0.003784962792 177
 
0.4%
0.0002138397058 10
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
1
23834 
0
22930 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

Length

2023-01-06T15:38:53.134303image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:53.528311image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

Most occurring characters

ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23834
51.0%
0 22930
49.0%

company_public_response_low_flag
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
44989 
1
 
1775

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

Length

2023-01-06T15:38:53.841006image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:54.220070image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44989
96.2%
1 1775
 
3.8%

company_freq
Real number (ℝ)

Distinct134
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.022993609
Minimum2.1383971 × 10-5
Maximum0.062334274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size365.5 KiB
2023-01-06T15:38:54.613436image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum2.1383971 × 10-5
5-th percentile8.5535882 × 10-5
Q10.001432726
median0.013044222
Q30.045890001
95-th percentile0.062334274
Maximum0.062334274
Range0.06231289
Interquartile range (IQR)0.044457275

Descriptive statistics

Standard deviation0.023431535
Coefficient of variation (CV)1.0190455
Kurtosis-1.3758817
Mean0.022993609
Median Absolute Deviation (MAD)0.012637927
Skewness0.54080906
Sum1075.2731
Variance0.00054903681
MonotonicityNot monotonic
2023-01-06T15:38:55.145086image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06233427423 2915
 
6.2%
0.05906252673 2762
 
5.9%
0.05788640835 2707
 
5.8%
0.05277563938 2468
 
5.3%
0.04589000086 2146
 
4.6%
0.04086476777 1911
 
4.1%
0.03889744248 1819
 
3.9%
0.02412111881 1128
 
2.4%
0.02275254469 1064
 
2.3%
0.02025062014 947
 
2.0%
Other values (124) 26897
57.5%
ValueCountFrequency (%)
2.138397058 × 10-5725
1.6%
4.276794115 × 10-5588
1.3%
6.415191173 × 10-5582
1.2%
8.55358823 × 10-5544
1.2%
0.0001069198529 515
1.1%
0.0001283038235 348
0.7%
0.000149687794 392
0.8%
0.0001710717646 400
0.9%
0.0001924557352 261
 
0.6%
0.0002138397058 350
0.7%
ValueCountFrequency (%)
0.06233427423 2915
6.2%
0.05906252673 2762
5.9%
0.05788640835 2707
5.8%
0.05277563938 2468
5.3%
0.04589000086 2146
4.6%
0.04086476777 1911
4.1%
0.03889744248 1819
3.9%
0.02412111881 1128
 
2.4%
0.02275254469 1064
 
2.3%
0.02025062014 947
 
2.0%

company_low_flag
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
24619 
1
22145 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

Length

2023-01-06T15:38:55.602720image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:56.087276image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

Most occurring characters

ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24619
52.6%
1 22145
47.4%

state_freq
Real number (ℝ)

Distinct58
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.052087772
Minimum-1
Maximum0.148084
Zeros0
Zeros (%)0.0%
Negative136
Negative (%)0.3%
Memory size365.5 KiB
2023-01-06T15:38:56.644757image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0.0047258575
Q10.017599008
median0.035240784
Q30.084937131
95-th percentile0.148084
Maximum0.148084
Range1.148084
Interquartile range (IQR)0.067338123

Descriptive statistics

Standard deviation0.073505087
Coefficient of variation (CV)1.4111774
Kurtosis119.54765
Mean0.052087772
Median Absolute Deviation (MAD)0.022346249
Skewness-8.236356
Sum2435.8326
Variance0.0054029978
MonotonicityNot monotonic
2023-01-06T15:38:57.199760image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1480839962 6925
 
14.8%
0.08944914892 4183
 
8.9%
0.08493713113 3972
 
8.5%
0.05758703276 2693
 
5.8%
0.04644598409 2172
 
4.6%
0.03633136601 1699
 
3.6%
0.0353904713 1655
 
3.5%
0.03524078351 1648
 
3.5%
0.03338037807 1561
 
3.3%
0.03246086733 1518
 
3.2%
Other values (48) 18738
40.1%
ValueCountFrequency (%)
-1 136
0.3%
2.138397058 × 10-51
 
< 0.1%
4.276794115 × 10-54
 
< 0.1%
0.0002352236763 11
 
< 0.1%
0.0002566076469 12
 
< 0.1%
0.0004062954409 19
 
< 0.1%
0.0007270549996 34
 
0.1%
0.000855358823 40
 
0.1%
0.0009195107348 43
 
0.1%
0.001069198529 50
 
0.1%
ValueCountFrequency (%)
0.1480839962 6925
14.8%
0.08944914892 4183
8.9%
0.08493713113 3972
8.5%
0.05758703276 2693
 
5.8%
0.04644598409 2172
 
4.6%
0.03633136601 1699
 
3.6%
0.0353904713 1655
 
3.5%
0.03524078351 1648
 
3.5%
0.03338037807 1561
 
3.3%
0.03246086733 1518
 
3.2%

state_null_flag
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
46628 
1
 
136

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

Length

2023-01-06T15:38:57.656242image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:58.058641image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46628
99.7%
1 136
 
0.3%

state_low_flag
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
42045 
1
4719 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

Length

2023-01-06T15:38:58.364487image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:38:58.759088image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

Most occurring characters

ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42045
89.9%
1 4719
 
10.1%

zipcode_freq
Real number (ℝ)

Distinct200
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00087150152
Minimum-1
Maximum0.015246771
Zeros0
Zeros (%)0.0%
Negative138
Negative (%)0.3%
Memory size365.5 KiB
2023-01-06T15:38:59.145144image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0.00032075956
Q10.0012616543
median0.0027799162
Q30.0056667522
95-th percentile0.010435378
Maximum0.015246771
Range1.0152468
Interquartile range (IQR)0.0044050979

Descriptive statistics

Standard deviation0.054552744
Coefficient of variation (CV)62.59627
Kurtosis331.41006
Mean0.00087150152
Median Absolute Deviation (MAD)0.0018176375
Skewness-18.224505
Sum40.754897
Variance0.0029760019
MonotonicityNot monotonic
2023-01-06T15:38:59.684771image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01524677102 713
 
1.5%
0.01191087161 557
 
1.2%
0.001389958087 520
 
1.1%
0.01103412882 516
 
1.1%
0.01058506543 495
 
1.1%
0.01043537764 488
 
1.0%
0.01011461808 473
 
1.0%
0.01007185014 471
 
1.0%
0.009900778377 463
 
1.0%
0.009858010435 461
 
1.0%
Other values (190) 41607
89.0%
ValueCountFrequency (%)
-1 138
0.3%
2.138397058 × 10-545
 
0.1%
4.276794115 × 10-568
 
0.1%
6.415191173 × 10-5102
0.2%
8.55358823 × 10-5120
0.3%
0.0001069198529 125
0.3%
0.0001283038235 204
0.4%
0.000149687794 196
0.4%
0.0001710717646 208
0.4%
0.0001924557352 144
0.3%
ValueCountFrequency (%)
0.01524677102 713
1.5%
0.01191087161 557
1.2%
0.01103412882 516
1.1%
0.01058506543 495
1.1%
0.01043537764 488
1.0%
0.01011461808 473
1.0%
0.01007185014 471
1.0%
0.009900778377 463
1.0%
0.009858010435 461
1.0%
0.008639124113 404
0.9%

zipcode_null_flag
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
46626 
1
 
138

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

Length

2023-01-06T15:39:00.134197image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:00.494929image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46626
99.7%
1 138
 
0.3%

zipcode_low_flag
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
37692 
1
9072 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%

Length

2023-01-06T15:39:00.819348image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:01.170708image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%

Most occurring characters

ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37692
80.6%
1 9072
 
19.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
1
38812 
0
7952 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Length

2023-01-06T15:39:01.522653image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:01.917021image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Most occurring characters

ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38812
83.0%
0 7952
 
17.0%

Older American
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
42511 
1
4253 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%

Length

2023-01-06T15:39:02.237336image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:02.631401image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42511
90.9%
1 4253
 
9.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
46196 
1
 
568

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Length

2023-01-06T15:39:02.953766image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:03.355464image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46196
98.8%
1 568
 
1.2%

Servicemember
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
43633 
1
 
3131

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Length

2023-01-06T15:39:03.653704image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:04.025290image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43633
93.3%
1 3131
 
6.7%

Closed
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
45497 
1
 
1267

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%

Length

2023-01-06T15:39:04.332679image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:04.696043image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45497
97.3%
1 1267
 
2.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
1
35619 
0
11145 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Length

2023-01-06T15:39:04.994986image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:05.374386image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Most occurring characters

ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 35619
76.2%
0 11145
 
23.8%

Closed with monetary relief
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
43295 
1
 
3469

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%

Length

2023-01-06T15:39:05.664819image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:06.054925image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%

Most occurring characters

ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43295
92.6%
1 3469
 
7.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
40723 
1
6041 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%

Length

2023-01-06T15:39:06.386880image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:06.775827image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%

Most occurring characters

ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40723
87.1%
1 6041
 
12.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size365.5 KiB
0
46396 
1
 
368

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46764
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Length

2023-01-06T15:39:07.074313image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-06T15:39:07.500684image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46764
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 46764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46396
99.2%
1 368
 
0.8%

Interactions

2023-01-06T15:38:33.819017image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:07.652557image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:11.413225image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:14.933797image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:18.614520image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:22.393856image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:26.517644image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:30.157242image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:34.268718image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:08.136003image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:11.873219image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:15.448141image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:19.087156image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:23.220089image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:26.976027image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:30.655505image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:34.702524image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:08.578136image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:12.291014image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:15.907344image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:19.521203image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:23.686123image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:27.457403image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:31.096754image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:35.161337image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:09.099370image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:12.750343image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:16.348760image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:20.003813image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:24.166586image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:27.890013image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:31.546028image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:35.620092image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:09.533758image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:13.176415image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:16.801620image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:20.448947image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:24.615721image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:28.331432image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:32.011725image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:36.093995image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:10.039471image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:13.633402image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:17.264774image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:20.987022image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:25.082313image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:28.809414image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:32.485930image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:36.567333image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:10.530270image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:14.083690image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:17.731189image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:21.494038image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:25.571527image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:29.242351image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:32.936935image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:37.003376image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:10.964037image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:14.517953image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:18.164268image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:21.960771image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:26.029511image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:29.722350image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-01-06T15:38:33.385233image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2023-01-06T15:39:07.941497image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
days_between_receipt_and_sentsub_product_freqissue_freqsub_issue_freqcompany_public_response_freqcompany_freqstate_freqzipcode_freqtimely_responseconsumer_disputed?sub_product_null_flagsub_product_low_flagissue_low_flagsub_issue_null_flagsub_issue_low_flagcompany_public_response_null_flagcompany_public_response_low_flagcompany_low_flagstate_null_flagstate_low_flagzipcode_null_flagzipcode_low_flagNot Older American, Not ServicememberOlder AmericanOlder American, ServicememberServicememberClosedClosed with explanationClosed with monetary reliefClosed with non-monetary reliefUntimely response
days_between_receipt_and_sent1.000-0.029-0.0520.027-0.047-0.150-0.015-0.0200.0430.0170.0070.0000.0000.0370.0160.0060.0320.0330.0000.0140.0000.0060.0000.0000.0000.0000.0130.0060.0210.0110.055
sub_product_freq-0.0291.0000.149-0.050-0.115-0.4830.005-0.0020.1110.0251.0000.1770.2010.1590.0120.1000.1060.4830.0000.0090.0000.0030.0070.0240.0200.0330.0960.0950.0580.1360.055
issue_freq-0.0520.1491.0000.5740.0510.1330.0170.0140.1560.0550.7220.1830.8970.7570.3140.1210.1290.4670.0200.0210.0190.0440.0350.0740.0440.0680.1010.1420.2500.1720.076
sub_issue_freq0.027-0.0500.5741.0000.0110.002-0.0090.0050.0970.0330.1590.1410.3311.0000.4340.0230.0660.0660.0090.0200.0080.0160.0080.0720.0160.0620.0260.0000.2270.1530.056
company_public_response_freq-0.047-0.1150.0510.0111.0000.2290.0030.0160.1040.0290.2660.0600.0610.1010.0791.0000.8840.3610.0160.0080.0150.0170.0120.0340.0000.0430.0670.0900.0680.1130.087
company_freq-0.150-0.4830.1330.0020.2291.0000.0290.0260.2070.0310.7560.1670.2970.6210.2480.4270.2010.9670.0200.0310.0190.0360.0240.0700.0230.0710.1320.1880.2480.2420.107
state_freq-0.0150.0050.017-0.0090.0030.0291.0000.4310.0090.0000.0000.0230.0120.0190.0220.0080.0190.0211.0000.3850.9930.1870.0190.0120.0210.0300.0000.0020.0090.0000.005
zipcode_freq-0.020-0.0020.0140.0050.0160.0260.4311.0000.0000.0000.0000.0160.0110.0080.0000.0080.0060.0090.9890.0160.9960.0260.0000.0080.0050.0060.0000.0000.0060.0020.000
timely_response0.0430.1110.1560.0970.1040.2070.0090.0001.0000.0310.1110.0060.0300.0970.0620.0800.0250.1790.0000.0080.0000.0000.0000.0220.0000.0170.0990.0780.0360.0470.483
consumer_disputed?0.0170.0250.0550.0330.0290.0310.0000.0000.0311.0000.0250.0000.0160.0330.0040.0200.0310.0070.0000.0040.0000.0160.0100.0040.0100.0130.0400.1140.0760.0910.049
sub_product_null_flag0.0071.0000.7220.1590.2660.7560.0000.0000.1110.0251.0000.1770.2010.1590.0120.1000.1060.4830.0000.0090.0000.0030.0070.0240.0200.0330.0960.0950.0580.1360.055
sub_product_low_flag0.0000.1770.1830.1410.0600.1670.0230.0160.0060.0000.1771.0000.2000.1410.0580.0530.0000.1250.0160.0000.0160.0000.0510.0060.0080.0640.0150.0350.0780.0220.005
issue_low_flag0.0000.2010.8970.3310.0610.2970.0120.0110.0300.0160.2010.2001.0000.3310.0470.0310.0380.0260.0110.0000.0110.0000.0020.0180.0130.0230.0450.0780.2050.0340.014
sub_issue_null_flag0.0370.1590.7571.0000.1010.6210.0190.0080.0970.0330.1590.1410.3311.0000.4340.0230.0660.0660.0090.0200.0080.0160.0080.0720.0160.0620.0260.0000.2270.1530.056
sub_issue_low_flag0.0160.0120.3140.4340.0790.2480.0220.0000.0620.0040.0120.0580.0470.4341.0000.0350.0450.0370.0000.0110.0000.0190.0120.0350.0050.0240.0000.0140.0720.0230.048
company_public_response_null_flag0.0060.1000.1210.0231.0000.4270.0080.0080.0800.0200.1000.0530.0310.0230.0351.0000.2020.0670.0080.0000.0080.0050.0080.0120.0000.0000.0160.0790.0340.1040.087
company_public_response_low_flag0.0320.1060.1290.0660.8840.2010.0190.0060.0250.0310.1060.0000.0380.0660.0450.2021.0000.1720.0060.0080.0060.0120.0000.0180.0000.0210.0420.0030.0130.0110.016
company_low_flag0.0330.4830.4670.0660.3610.9670.0210.0090.1790.0070.4830.1250.0260.0660.0370.0670.1721.0000.0100.0170.0090.0190.0000.0550.0110.0550.1060.0390.0440.0910.094
state_null_flag0.0000.0000.0200.0090.0160.0201.0000.9890.0000.0000.0000.0160.0110.0090.0000.0080.0060.0101.0000.0170.9890.0260.0000.0090.0050.0060.0000.0000.0070.0010.000
state_low_flag0.0140.0090.0210.0200.0080.0310.3850.0160.0080.0040.0090.0000.0000.0200.0110.0000.0080.0170.0171.0000.0160.2990.0220.0080.0320.0300.0000.0130.0050.0060.010
zipcode_null_flag0.0000.0000.0190.0080.0150.0190.9930.9960.0000.0000.0000.0160.0110.0080.0000.0080.0060.0090.9890.0161.0000.0260.0000.0080.0050.0060.0000.0000.0060.0020.000
zipcode_low_flag0.0060.0030.0440.0160.0170.0360.1870.0260.0000.0160.0030.0000.0000.0160.0190.0050.0120.0190.0260.2990.0261.0000.0290.0140.0070.0230.0050.0000.0000.0000.005
Not Older American, Not Servicemember0.0000.0070.0350.0080.0120.0240.0190.0000.0000.0100.0070.0510.0020.0080.0120.0080.0000.0000.0000.0220.0000.0291.0000.6990.2450.5920.0000.0050.0060.0000.000
Older American0.0000.0240.0740.0720.0340.0700.0120.0080.0220.0040.0240.0060.0180.0720.0350.0120.0180.0550.0090.0080.0080.0140.6991.0000.0340.0840.0140.0020.0190.0110.011
Older American, Servicemember0.0000.0200.0440.0160.0000.0230.0210.0050.0000.0100.0200.0080.0130.0160.0050.0000.0000.0110.0050.0320.0050.0070.2450.0341.0000.0290.0100.0000.0100.0000.005
Servicemember0.0000.0330.0680.0620.0430.0710.0300.0060.0170.0130.0330.0640.0230.0620.0240.0000.0210.0550.0060.0300.0060.0230.5920.0840.0291.0000.0050.0000.0280.0120.000
Closed0.0130.0960.1010.0260.0670.1320.0000.0000.0990.0400.0960.0150.0450.0260.0000.0160.0420.1060.0000.0000.0000.0050.0000.0140.0100.0051.0000.2980.0470.0640.013
Closed with explanation0.0060.0950.1420.0000.0900.1880.0020.0000.0780.1140.0950.0350.0780.0000.0140.0790.0030.0390.0000.0130.0000.0000.0050.0020.0000.0000.2981.0000.5060.6880.159
Closed with monetary relief0.0210.0580.2500.2270.0680.2480.0090.0060.0360.0760.0580.0780.2050.2270.0720.0340.0130.0440.0070.0050.0060.0000.0060.0190.0100.0280.0470.5061.0000.1090.024
Closed with non-monetary relief0.0110.1360.1720.1530.1130.2420.0000.0020.0470.0910.1360.0220.0340.1530.0230.1040.0110.0910.0010.0060.0020.0000.0000.0110.0000.0120.0640.6880.1091.0000.034
Untimely response0.0550.0550.0760.0560.0870.1070.0050.0000.4830.0490.0550.0050.0140.0560.0480.0870.0160.0940.0000.0100.0000.0050.0000.0110.0050.0000.0130.1590.0240.0341.000

Missing values

2023-01-06T15:38:37.879092image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-01-06T15:38:40.125668image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

consumer_complaint_narrativetimely_responseconsumer_disputed?days_between_receipt_and_sentsub_product_freqsub_product_null_flagsub_product_low_flagissue_freqissue_low_flagsub_issue_freqsub_issue_null_flagsub_issue_low_flagcompany_public_response_freqcompany_public_response_null_flagcompany_public_response_low_flagcompany_freqcompany_low_flagstate_freqstate_null_flagstate_low_flagzipcode_freqzipcode_null_flagzipcode_low_flagNot Older American, Not ServicememberOlder AmericanOlder American, ServicememberServicememberClosedClosed with explanationClosed with monetary reliefClosed with non-monetary reliefUntimely response
0Dear Sir or Madam, Ever since XXXX XXXX XXXX sold our Mortgage Loan to XXXX, we have had nothing but problems. My husband and I back in 2009, tried to modify the loan. This was an absolute nightmare. After submitting information several times and going through numerous " scheduling '' of calls with Loan counselors, who when I finally got to talk to them, had nothing of substance to discuss or help me with and offered no guidance or help. They would tell me that I needed to get certain pieces of info. and schedule yet another call ( which were always 2 weeks later ) and take it from there, then it was like XXXX XXXX XXXX ... .. I would schedule call after call just to discuss separate pieces of my Loan Mod. Application. It made NO SENSE! I got nowhere and gave up. I have a file 3 inches thick with my application, with forms and notes and all the back up info that I scanned to them, which they claimed to never have received ... .. I finally gave up. With my husband laid off due the construction industry being very slow at the time, I decided to file bankruptcy. I believe that had I was given the chance to modify, I could have avoided filing for Chapter XXXX. About 4 years later or so, here I am now, and the loan was sold to Nationstar. Again, I am having issues which again stem from XXXX. I have had to have my bankruptcy attorney help me to get a simple answer about why my escrows all of the sudden went up {$300.00} per month! My taxes did not go up. The only thing that I did do was switch my Homeowners Insurer and my payment should have only gone up around {$30.00} a month, or less!! XXXX sent me XXXX copies of an Escrow Analysis which was XXXX or so pages, which raised my payment upwards of {$300.00} per month, and did not offer a clear reason why. I called and was given no explanation by XXXX. As a matter of fact, I was told " you were not supposed to see that ''. I did not know what that meant. I received a letter from XXXX after this saying my loan was transferred to NationStar. I called them for explanation and guidance, and got fuzzy answers from them. Nobody could explain the payment increase. They even told my attorney that they did not know what happened. I kind of let it go for a while, and then when I called in my payment for that month they would not take my normal payment. They would only take the payment with the increase of {$300.00}. I did not want to pay that because I did not agree with it and it is not in my budget being in Chapter XXXX, plus I was offered no reason why the payment increased! So, for the next several months I had to mail in my payments ( my normal payment NOT the payment with their increase calculations ), and my payments were late. In the meantime, I am having an attorney help me. After approximately 7 months, my attorney FINALLY got an answer ... .. my payment did increase but buy {$90.00}, not {$300.00} - however, I still do not why! I have the form and my loan number is crossed out, so I do n't even know if it is mine .... Right now, I am so confused. I have now incurred attorneys fees and late fees due to this error. I do not think I should be obligated to pay these fees due to XXXX error and Nationstar 's ignorance in its inability to explain the increase. Is there anything you can do to help me. \n1000.098495000.0978320-1.00000010-1.000000100.02020800.018711000.00119800100001000
1on XXXX XXXX, 2015 there was an ACH transaction withdrawal from my account without my permission for {$750.00} to a company bamed XXXX. this ACH transaction caused my business account to go into a negative balance. when I noticed the transaction on XXXX XXXX, 2015 I immediately called my bank and spoke to the claims department. I explain the situation that this was a fraudulent activity that I have no knowledge or no relations to XXXX or the bank that was involved as well named fifth third Bank in Michigan. XXXX XXXX filed the claim XXXX XXXX filed the claims for me and told me I would receive a refund in 12 hours or up to 1 to 2 business days. When I followed up on XXXX XXXX, 2015 with XXXX who holds my business account at approximately XXXX XXXX I was told that my claim was denied because I needed to make a claim within 24 hours of the transaction. before finding out that my claim was denied I have been going back-and-forth with the XXXX the claim department and the claim department from fifth third Bank. From here I was able to claim the company ID and the trace number in regards to this transaction. after finding out that my claim was denied I had spoke to my branch manager at XXXX to have a representative called the claim department in regards to the situation. I was able to retrieve my contract that I had signed with the business account. On Monday, XXXX XXXX, 2015 I have to call the XXXX claim department and they will be contacting fifth third bank with me on the line in regards to this transaction. I have filed a claim two times more after the my claim was denied. \n1000.019973000.0207420-1.00000010-1.000000100.00303710.089449000.00985800100001000
2My wife has not received a paper bill from Chase Card Services for an Amazon account in two years. I was informed that the account had paperless billing. The card is basically maxed out with late fees despite receiving payments and I had no idea. \n100-1.000000100.0182830-1.00000010-1.000000100.03889700.017599000.00243800100001000
3the company m & M funding has been harassing from the time i bought my first vehicle in 2011 from them the would call me when the declaration page on my insurance would expire instead of calling the insurance company they also lied to me had me pay for gap on my vehicle than when my son wrecked my vehicle they told me they were not doing gap because of the payment process of gap they call me when im at work all the time im about ready to be fired i can not answer my phone at work there former manager told me XXXX time that he did n't think i had insurance because he was having a hard time getting the declaration page from the insurance company he basically said i was lying he told me his daughter worked for the same insurance company i had and i and i lying about how long it was going to take for me to get the paperwork i talked to XXXX at the company on XXXX/XXXX/2015 at XXXX our time and than he called me again today for the same thing i already talked to him about i would like to own both of my vehicles from this company there is other things they have called continuously about but i ca n't remember than all right now. they are also very rude with there clients they are always got new employees so you never know who your talking to from XXXX month to the next so everyone at the company knows your business its not just XXXX person working on the file. \n1060.005902010.02001500.00254501-1.000000100.00002110.016786000.00171100100001000
4Can my reverse mortgage lender refuse to continue/renew my current property tax loan? \n\nHi, My lender, Wells Fargo, is telling me that they can not continue/renew my current loan that they had advanced for property taxes that were due. They have informed me that, unless I repay the full balance, they will begin foreclosure proceedings on my home now. I am told that HUD XX/XX/2015 issued new rules to lenders affecting reverse mortgage loans. Specifically, in my case, I now no longer meet the " XXXX '' requirement ; I am told that I am at XXXX %. \n\nI am XXXX years old and do n't want to lose my home. My husband XXXX last year, he was XXXX and had XXXX XXXX. We have never been late on any payments to Wells Fargo, and I can comfortably meet all my expenses, including the payment that I make to Wells Fargo for back property taxes each month. \n\nThis change of rules came as a total surprise. I hate to say this, but I feel that I have been misled, unwittingly perhaps. To their credit, Wells Fargo has assigned a financial counselor to my case, XXXX XXXX, which I appreciate. I am told by XXXX XXXX, this HUD rule change is not only a problem for me but also pertains to many other seniors in our country who have property tax and/or home insurance advances from their lenders. I suspect that many of these seniors are not able to speak up for themselves and will, indeed, loose their homes. \n1010.017449000.0247410-1.000000100.055727000.04589000.003143010.00012801000101000
5after more than 7 years from the date of our delinquency on our XXXX mortgage and having no contact from any one attempting to collect the debt after we lost our home in a foreclosure in XXXX we suddenly have a company trying to collect the debt and they are the first company to report this debt on our credit report. We filed for bankruptcy in after our home was foreclosed on and the original creditor did not, to my knowledge, file a proof of claim- they just charged off the account since they could not collect on the sale proceeds at foreclosure They also are reporting that payments were made on the account in XXXX but our last payment before trying to negotiate a modification was in XXXX of XXXX and the home was sold at a foreclosure sale in XXXX. They may have bought the debt from some one in an attempt to collect but the statute of limitations has expired for legal action as well as the 7 year statute for reporting it on our credit report- some one has re-aged the debt by stating that there were payments made in XXXX but XXXX records show that the property was sold long before XXXX. Since our date of delinquency was in XXXX of XXXX should n't we have the right to have it removed from our credit reports .No reporting of this debt was ever on our credit report until XXXX \n1100.005538010.11198800.004298010.098837000.01629500.016786000.00410600010001000
6On XXXX XXXX 2014, a car dealership ran my credit XXXX times in 1 day by mistake. They thought my dad was me and kept running my credit trying to get my father a loan. so I never tried to get any loans so my credit should n't have been ran XXXX times. so all XXXX credit inquires on XXXX/XXXX/14 are not mine and should not be on my credit report \n101-1.000000100.12496800.03951800-1.000000100.06233400.007891010.00126200100001000
7Received a promotional offer to deposit XXXX free miles into my Spirit Airlines account that never materialized despite my opening an account with Spirit Airlines and linking to my XXXX. Never received any additional miles for any purchases for the life of the card. Poor customer service and response time. When I requested to close my account, I was transferred by a rep named XXXX to a woman named XXXX and XXXX told me she could n't assist with that request. Poor customer service is an understatement for this particular credit card company. And false advertising on promotional sign-up benefit. \n100-1.000000100.0127660-1.000000100.287679000.05277600.018711000.00124000100000010
8I signed up for the promotional rate of 0 % on XXXX/XXXX/15 for 21 months and there was a 2 % charge at that time for the balance transfer. Chase is stating that I signed up for a 0.99 % rate for 7 months which I have never signed up for such a short term promotion in my life. I was not paying attention to the .99 % interest they were charging but when It jumped up to 10 % I noticed. I consider this a bait and switch. \n100-1.000000100.0058161-1.00000010-1.000000100.03889700.148084000.00757000100001000
9Scottrade Bank Manager XXXX XXXX XXXX instructed me to provide me personal information in a manner that is insecure ( via unencrypted email ). Roughly 10 days after providing the information as XXXX XXXX 's request, my account was hacked. Scottrade refused to make my account whole and said I was responsible for the hack. \n\nTo warn other consumers, do not trust this company. At the current time Scottrade will not even address my concerns. \n\nAttached is the correspondence between myself and XXXX XXXX. \n1100.057181000.0332310-1.00000010-1.000000100.00269410.148084000.00322900100010000
consumer_complaint_narrativetimely_responseconsumer_disputed?days_between_receipt_and_sentsub_product_freqsub_product_null_flagsub_product_low_flagissue_freqissue_low_flagsub_issue_freqsub_issue_null_flagsub_issue_low_flagcompany_public_response_freqcompany_public_response_null_flagcompany_public_response_low_flagcompany_freqcompany_low_flagstate_freqstate_null_flagstate_low_flagzipcode_freqzipcode_null_flagzipcode_low_flagNot Older American, Not ServicememberOlder AmericanOlder American, ServicememberServicememberClosedClosed with explanationClosed with monetary reliefClosed with non-monetary reliefUntimely response
46754Experian has listed on my credit report a debt that was abolished by XXXX XXXX in XXXX 2013. This was a joint account as I co-signed for a coworker to purchase a used car. XXXX XXXX agreed to relieve me of all financial obligation, garnishments, and prompt deletion of credit entries in exchange for a one-time payment of {$3000.00}. The payment was immediately rendered and the stipulations were signed by a judge of the XXXX County District Court that same month. Experian keeps verifying the debt as valid because XXXX XXXX is supplying fictitious information because collection efforts remain in effect for XXXX party on account. XXXX County District Court has assured me that they do not verify debts, make entries to credit reports or make deletions. \nXXXX also has an account listed by XXXX XXXX in the amount of {$81.00}. This account was paid directly to XXXX several months ago. I was never contacted by XXXX by any means. The representative that I spoke with said the account would be deleted but she could not send in writing. She referred me to a website to print a paid letter. I have proof that I paid XXXX directly. \nXXXX is also listing the erroneous account by XXXX XXXX as past due in the amount of {$1500.00}. XXXX also has several collection accounts that have been paid and I have provided written proof supplied by the collection agency for medical bills. The companies are XXXX XXXX XXXX XXXX XXXX and XXXX collections. The collection companies agreed to delete the entries electronically but they remain on my credit file. \nAdditionally, XXXX XXXX XXXX has an open claim with XXXX XXXX for damages on a vehicle that I rented in South Dakota from XX/XX/XXXX thru XX/XX/XXXX while on of several travel contracts for work at XXXX XXXX XXXX. I was never notified and allowed to investigate the validity of the debt. When I realized it on my credit report, I called XXXX XXXX and spoke with XXXX XXXX who agreed to delete the entry if I paid her because she did not believe the XXXX would pay the " extra fees ''. The was minor under baggage damage that was not visible to me when the vehicle was returned. I was made aware of the collection efforts when I checked my credit earlier this year. This account appears on my Experian credit report and was verified as valid. I never received notice of the debt. I was never allowed to investigate the validity of the alleged debt. \nLastly, XXXX XXXX XXXX was paid {$720.00} in XX/XX/XXXX in an effort to have them remove a collection from my XXXX and Experian credit reports. Despite me never contracting with company I paid them because XXXX refused to collect the monies owed to them. I now have a delinquent XXXX entry and a XXXX XXXX collection account for the same debt. I have made several calls to request deletion of improper entry to my credit report but was told it is not their policy to delete especially since I had already paid. I never received notices. The item just appeared on my credit report. I was never allowed to validate the debt. \n100-1.000000100.12496800.017727000.287679000.05906300.029488000.00406300100000010
46755I applied for a loan with company and was approved with a initial credit limit of {$650.00} that I could take out cash advances out against so I requested a {$400.00} dollar advance and was approved and I received emails showing all this from company but when it came time to fund account instead of money all of sudden they decide I do n't qualify even though they had my social security number and done check from beginning and still approved it first time should have not been rejected this is fraud doing it based on age .Also I offer to send in all papers showing income and my identity for proof based on letter but they said no which I had no problem faxing the papers to them. \n1100.024805000.00057710.000492010.098837000.00132610.017599000.00134700001001000
46756I received a call ( XXXX ) from Trinity and Hope Associates on XXXX/XXXX/2015 about a bill in the amount of {$610.00} owed. I asked to check with insurance ( XXXX XXXX XXXX XXXX XXXX South Carolina ) on the issue and gentleman replied he would not that I refused to pay and hung up. I called back and got recording. I left message stating that I did n't refuse payment I had simple ask to check with insurance for more information. On XXXX/XXXX/2015 obtained original number and information on matter from XXXX Hospital and was advise to submit to insurance to see why not paid and to call central billing ( XXXX ) It was then I encountered XXXX from Trinity and Hope. She accessed my files and said the amount owed was {$1100.00}. Since I had no record of bill I agreed to pay amount with my XXXX XXXX Card, fearing that case would be turned over to attorney and fees and penalties would incur according to XXXX. XXXX then conferenced in a representative from my insurance company, XXXX, and while pretending to be canceled by previous request for insurance to submit for insurance to pay. XXXX seemed suspicious but with proof cancel the request to submit. I then paid amount {$1100.00} not remembering the call from day before that quoted {$610.00} XXXX promised to call back the next evening with her associates name XXXX to request reimbursement from my insurance company for the payment made to her company. I have not heard from Trinity and Hope since. Feeling uneasy about situation I called XXXX XXXX that same evening and found that the only charge pending for that day was {$1500.00} to XXXX XXXX XXXX XXXX, name that was never mentioned in call to XXXX. Only Trinity and Hope Associates was mentioned. I was advised by XXXX XXXX to wait until charge was posted before I disputed it. This is what I did, submitting to them all paperwork on this matter. Finding bill from hospital in the amount of {$610.00} I was willing to dispute only the excess charge over that amount however after calling insurance and learning there was never a request for payment from hospital in my name or the billing account listed I decide to dispute the entire {$1500.00} that was charged. My insurance is looking into that matter. \n0000.041357000.02489100.01813400-1.000000100.00002110.032461000.00119800100000001
46757The XXXX XXXX BB & T offer I opened a XXXX account for was 90 days of triple points for new XXXX card accounts. At about 70 days, the triple points stopped being posted to my account. I contacted them and they said that the triple point days begin on the day they internally " approved '' the application in their process. However I did n't received the credit card until 2 weeks later and immediately activated it. No one can possibly use a credit card before they even get it. To base the start date on the day the application is " internally approved '' at BBT means the customer will never be able to get 90 days triple points and is dishonest. \n110-1.000000100.0056451-1.000000100.287679000.00442610.013664000.00226700100001000
46758American Express ( Amex ) failed to follow their term in their letter dated XXXX/XXXX/2015 ( copy sent earlier ). All their past responses to this complaint are irresponsible. Therefore, I will continue to file this complaint until Amex becomes responsible and transfers the XXXX earned rewards points to my open Amex account. \n\nI am in full disagreement with Amex 's failure to transfer XXXX earned points from my closed Amex account # XXXX to my open Amex account # XXXX ( copies sent earlier ), because Amex stated in their XXXX/XXXX/2015 letter, " that as per the XXXX Terms and Conditions if you cancel your enrollment in the program and do n't keep open any American Express Cards, all points in your program account will be immediately forfeited ''. The key word in this quote is the word " any '', which pertains to my open Amex account # XXXX. On XXXX/XXXX/2015 I advised Amex in my letter ( copy sent earlier ) of this open Amex account. \n\nAmex needs to transfer my earned XXXX points to my open Amex account # XXXX per their terms and conditions. If then they are not in compliance with Federal banking laws. \n100-1.000000100.0127660-1.00000010-1.000000100.01122700.057587000.00117600001001000
46759We took an equity line with Citizens Bank in XX/XX/XXXX. After a long process to get this loan we signed the paperwork in XX/XX/XXXX. We then used the money to pay contractors to do some work on our home. The paperwork was " lost '', " not processed '' or just misplaced and we had to duplicate some of this paperwork for months after the loan was originated. The payment set up was incomplete which caused headaches and late charges which after a full year the bank realized their errors and reversed all those charges and cleaned the record. In XX/XX/XXXX I refinanced my home and closed the equity line. Unbeknownst to me or my wife was that Citizens slipped a line in the documents to charge {$350.00} for early termination of the equity line if closed within three years. I only found this out when I received a statement showing my payment for this. They also charge us a yearly fee to have the loan " open '' which they did not prorate for the 4 months we did not use. I have complained to the bank about this and that the loan officer did not explain this fee prior to the loan being opened. On top of this they also charged {$25.00} for a fax to get the payoff of the loan. The bank refuses to give a refund for the {$350.00} or the prorated fee for the loan or the {$25.00} for a fax fee that was also never discussed. {$25.00} for a fax seems a bit high, almost a price gouging situation. The bank personnel have told me they would return calls several times within 24-48 hours and yet have taken over a week on each occasion to reply to me with the same negative response about reimbursing my fees that were paid. Had I been aware of the {$350.00} fee I could have kept the loan " open '' until XXXX with a minimum balance to avoid these fees. I was not given that opportunity to do this and the statement I received was weeks after the payment was made making this situation even that much more frustrating. \n1100.014648000.0245270-1.00000010-1.000000100.00348610.018711000.00147500100001000
46760I filed chapter XXXX bankruptcy in XXXX 2012. I included in my bankruptcy a bill from a company named XXXX. The bill was for residential garbage collection from my house that was vacant and being foreclosed. \nXXXX has given the bill to a collection company named Puget Sound Collections and they are currently trying to collect the amount past due. \nI 've contacted Puget Sound Collections several times and let them know this bill was part of a chapter XXXX bankruptcy filing. I 've even sent a copy of the list of creditors from my bankruptcy to Puget Sound Collections. It clearly states that this bill was part of my bankruptcy. \nThey refuse to remove this from my credit report. It 's causing severe damage to my credit score and am in need of assistance getting Puget Sound Collections to remove this from my credit report. \n1100.079014000.11198800.004298010.287679000.00006410.011697000.00145400100001000
46761I have a reverse mortgage with Champion Mortgage. I started the reverse mortgage with XXXX XXXX and was very up front with them about me NOT living in the home, but DO live across the street. I was told 'we'llcross that bridge when we come to it. ' We NEVER came to it. NowChampion wants to foreclose due to me not living in the house. I have been talking to Champion since XX/XX/XXXX to attempt to get this corrected, and everytime I call I get some XXXX new and have to start at square XXXX. Attachedplease find a time line of my contacts the Champion. I do have a cashcontract by way of my broker for {$150000.00}, in Champion 's possessionsince XX/XX/XXXX. Today XX/XX/XXXX I called their 'short sale specialist'XXXX for the second time in XXXX days getting her voice mail asking for areturn call, but that has not happened as yet. I called XXXX XXXX of Virginia and his office contacted HUD and FTC on my behalf. \nI was granted a thirty day postponement on the foreclosure set for XX/XX/XXXX. I have, in my possession as does XXXX XXXX, XXXX appraisals, XXXX from XX/XX/XXXX for {$140000.00} and a second from XXXX for {$170000.00}. Surprisingly the house grew by XXXX square foot in the time between appraisals, without a building permit. \n1000.001839010.0771960-1.00000010-1.000000100.02020800.033380000.00141100010001000
46762Bank of America is my investor for my XXXX mortgage and XXXX XXXX is my servicer. No one seems to be able to tell me why I did n't qualify for the National Mortgage Settlement to lower my principal or get refinanced for a lower interest for my XXXX mortgage that is owned by Bank of America. I would like to be able to refinance for today 's low rates per the settlement agreement. I keep getting the run around and was actually told by a Bank of America employee that Bank of America does not own any loans and that I must be mistaken. \n1020.098495000.0245270-1.000000100.287679000.05277600.030814000.00269400100001000
46763I filed a complaint with the CFPB last year in regards to my chase private student loans and my inability to repay at the current monthly payment. Chase was willing to negotiate to a certain extent and granted me a temporary deferment period. My request to Chase was to lower my monthly payments which was disregarded and as a last resort I signed the deferment paperwork to get some relief. The paperwork that was sent to me was requested to be returned by Chase, even the paperwork with new loan terms which they would not allow me to keep. I sent all signature pages in but they would not grant the deferment until I sent in all the paperwork including the new terms of the loan. I currently have no documentation showing the new loan terms after the papers were signed let alone what my monthly payment will be. I sent in a letter to CSL on XXXX/XXXX/15 requesting to lower my monthly payments being that the deferment period was coming to end relatively soon - I did not get a response from Chase. I made it as clear as I possibly could that I would not be able to afford these monthly payments for the next 20 years. I have no way of paying the original monthly payment and Chase has not provided any documentation showing my new monthly payment. \n1000.036481000.01043500.00423401-1.000000100.03889700.035241000.00748400100001000

Duplicate rows

Most frequently occurring

consumer_complaint_narrativetimely_responseconsumer_disputed?days_between_receipt_and_sentsub_product_freqsub_product_null_flagsub_product_low_flagissue_freqissue_low_flagsub_issue_freqsub_issue_null_flagsub_issue_low_flagcompany_public_response_freqcompany_public_response_null_flagcompany_public_response_low_flagcompany_freqcompany_low_flagstate_freqstate_null_flagstate_low_flagzipcode_freqzipcode_null_flagzipcode_low_flagNot Older American, Not ServicememberOlder AmericanOlder American, ServicememberServicememberClosedClosed with explanationClosed with monetary reliefClosed with non-monetary reliefUntimely response# duplicates
23I have sent several requests to Experian requesting an investigation of my accounts. It has been months and I still have not received a response to my concerns. The only thing I have received is some automated rejection letter stating that they wo n't do anything to help me ( please see attached ). \nThis has to be a violation of my rights. I feel like I 've already wasted so much time just trying to get Experian to look at the errors on my credit report and I 'm so frustrated that Experian is intentionally not responding to my inquiries. I need to have this issue resolved immediately. There are many things I need to do with my life and they all involve my credit. But I am not able to move forward all because of this credit bureau! \n100-1.000000100.02953100.011376000.287679000.05906300.015995000.0099010010000100013
59While checking my personal credit report, I noticed an unauthorized and fraudulent credit inquiry made by XXXX on or about XX/XX/XXXX on Transunion. I did not authorized anyone employed by this company to make any inquiry and view my credit report. XXXX has violated the Fair Credit Reporting Act Section 1681b ( c ). They were not legally entitled to make this fraudulent inquiry. This is a serious breach of my privacy rights. \nI have requested that they mail me a copy of my signed authorization form that gave them the right to view my credit within five ( 5 ) business days so that I can verify its validity and advised them that if they can not provide me with proof that I authorized them to view my credit report then I am demanding that they contact the credit bureaus immediately and have them remove the unauthorized and fraudulent hard inquiry immediately. I also requested that they remove my personal information from their records. My Social Security # is XXXX and my Date of Birth is XX/XX/XXXX in case it is needed to locate the fraudulent inquiry in their system. \n101-1.000000100.01032800.009601010.287679000.05788600.148084000.007356000001010009
12I am requesting that EXPERIAN immediately delete the address listed on my credit file as reported and previously listed on the EXPERIAN Credit File as : XXXX XXXX XXXX XXXX XXXX WA XXXX. Address indentification number : XXXX, Geographical code : XXXX \n100-1.000000100.12496800.010628000.287679000.05906300.022881000.004833001000000106
43This is a formal complaint against TRANSUNIONAccording to my credit report, XXXX is currently reporting to TRANSUNION that I applied for credit with XXXX on XXXX/XXXX/2014 I did not grant TRANSUNION authorization to provide access to my credit report to XXXX ; or share my credit report with XXXX. \n\nThe Fair Credit Reporting Act requires that a creditor be able to verify the written authorization of the consumer giving the creditor permission to review their credit. If you can provide a copy of a credit application authorizing the disclosure of my credit files with my signature, I will accept the inquiry. If a signed authorization can not be found please remove the inquiry. \n\nThe presence of this inquiry is adversely affecting my credit report. Time is of the essence so I would greatly appreciate a response from you immediately. Please mail me the copy of a signed application or a letter indicating your intention to delete the inquiry. \n110-1.000000100.01032800.009601010.287679000.05788600.022881000.004833001000010006
58While checking my personal credit report, I noticed an unauthorized and fraudulent credit inquiry made by XXXX on or about XX/XX/XXXX on Experian. I did not authorized anyone employed by this company to make any inquiry and view my credit report. XXXX has violated the Fair Credit Reporting Act Section 1681b ( c ). They were not legally entitled to make this fraudulent inquiry. This is a serious breach of my privacy rights. \nI have requested that they mail me a copy of my signed authorization form that gave them the right to view my credit within five ( 5 ) business days so that I can verify its validity and advised them that if they can not provide me with proof that I authorized them to view my credit report then I am demanding that they contact the credit bureaus immediately and have them remove the unauthorized and fraudulent hard inquiry immediately. I also requested that they remove my personal information from their records. My Social Security # is XXXX and my Date of Birth is XX/XX/XXXX in case it is needed to locate the fraudulent inquiry in their system. \n102-1.000000100.01032800.009601010.287679000.05906300.148084000.007356000001000106
27I never received any communication from this company that my account will be send to collection without my knowledge. Do n't even know this company and find out get bad review with XXXX. \n1100.055983000.04432900.003721010.098837000.00017110.011718000.000748011000010005
31In XXXX, I requested my free annual credit report. After viewing my credit report, I noticed over XXXX credit/loan inquiries on my account that was not authorized by me. I contacted each company and was told that there was not any account open under my information. I explained that I have a hard inquiry on my credit report and need it removed as soon as possible so that I could apply for a home. I was told that the inquiries would be removed from my credit report. As of XXXX/XXXX/XXXX, none of the inquiries have been removed dating back to XXXX. I had a initial fraud alert placed on my report on XXXX XXXX, so if any credit reports are being pulled with my information, I was to be contacted by the company before any action was taken place. I just want the inquiries to be removed so that my scores and credit is not being impacted any longer. I would like to purchase a house, but until all of the inquires are removed I will not be approved with XXXX inquires on my credit report. \n103-1.000000100.12496800.03951800-1.000000100.06233400.046446000.000642011000010005
42This is a formal complaint against TRANSUNIONAccording to my credit report, XXXX XXXX is currently reporting to TRANSUNION that I applied for credit with XXXX XXXX on XXXX/XXXX/2015 I did not grant TRANSUNION authorization to provide access to my credit report to XXXX XXXX ; or share my credit report with XXXX XXXX. \n\nThe Fair Credit Reporting Act requires that a creditor be able to verify the written authorization of the consumer giving the creditor permission to review their credit. If you can provide a copy of a credit application authorizing the disclosure of my credit files with my signature, I will accept the inquiry. If a signed authorization can not be found please remove the inquiry. \n\nThe presence of this inquiry is adversely affecting my credit report. Time is of the essence so I would greatly appreciate a response from you immediately. Please mail me the copy of a signed application or a letter indicating your intention to delete the inquiry. \n110-1.000000100.01032800.009601010.287679000.05788600.022881000.004833001000010005
0A few months ago I ended up filing some disputes because there was incorrect and incomplete information on my credit report. So I prepared a nice letter and sent it with a copy of my driver 's license, proof of my social security number and proof of my mailing address so that Experian would be able to verify my identity. \nIt has been at least 2 months since I mailed my letter and I have n't heard back. When I try calling their XXXX number they want a report number before I speak with an agent and since I do n't have XXXX I ca n't speak to anyone. \nI thought that the credit companies had to respond back to me within 30 days otherwise they are supposed to remove things from my credit report?! \nWell it 's been way more than 30 days and all of the stuff I disputed is still there. I know I can go online and buy a credit monitoring service and try to dispute things online but I thought that Experian is supposed to help me for free! \nI 'm at the point where I 'm done wasting time and need to get this fixed immediately. \n100-1.000000100.02953100.011376000.287679000.05906300.015995000.009901001000010004
3A few months ago I requested my credit report from Experian. I got back this letter from them telling me that they received something that looked like fraud. I did n't get a chance to call them right away and I honestly thought it was some kind of mistake so I just went online and got my report from some website instead. \nI ended up filing some disputes because there was incorrect and incomplete information on my credit report. So I prepared a nice letter and sent it with a copy of my driver 's license, proof of my social security number and proof of my mailing address so that Experian would be able to verify my identity. \nIt has been at least XXXX months since I mailed my letter and I have n't heard back. When I try calling their XXXX number they want a report number before I speak with an agent and since I do n't have XXXX I ca n't speak to anyone. \nI thought that the credit companies had to respond back to me within XXXX days otherwise they are supposed to remove things from my credit report?! \nWell it 's been way more than XXXX days and all of the stuff I disputed is still there. I know I can go online and buy a credit monitoring service and try to dispute things online but I thought that Experian is supposed to help me for free! \nI 'm at the point where I 'm done wasting time and need to get this fixed immediately. \n100-1.000000100.02953100.011376000.287679000.05906300.015995000.009901001000010004